e-ISSN 2231-8526
ISSN 0128-7680

Home / Regular Issue / JST Vol. 29 (4) Oct. 2021 / JST-2553-2021


The Demand Model of App-Based Transportation Household Scale in Semarang, Indonesia

Anita Ratnasari Rakhmatulloh, Diah Intan Kusumo Dewi, Wijayanti and Rosna Sari Pulungan

Pertanika Journal of Science & Technology, Volume 29, Issue 4, October 2021


Keywords: App-based transportation, demand, household unit

Published on: 29 October 2021

In the development of transportation systems, Application-Based Transportation is an innovation to adapt to technological advances. It offers users an alternative mode that is cheap, easy, and flexible according to their needs. The Application-based travel demands can be seen from its socio-economic and travel characteristics. In Indonesia, previous studies have concentrated on study areas on a city scale, with diverse land use classifications not only on the residential area which is the most users of app-based transportation. The modelling results in this study were obtained from spatial simulation and partial linear regression analysis with the T-test as the final stage of analysis. As a result, demand for App-Based Transportation is affected by two factors which include age and travel costs. They are inversely proportional to the frequency of travel. In this case, this mode is mostly used by the population with young age and low cost of travel. Also, this mode is only used on short-distance trips and trips during rush hour in the morning. During the afternoon rush hour, the trip is transferred to public transportation, which has a lower cost. Therefore, this study aims to determine the application-based transportation demand model for household units in Tlogosari, Semarang, Indonesia. An additional in-depth study is needed to be carried out on the degree of motorcycle safety to improve services.

  • Adam, M., Kee, D. M. H., Junaina, I., Fadhilah, N., Uwais, N., Al Rashidi, F., Al Shammari, H., Quttainah, M. A., Srivastava, A., & Pandey, R. (2020). The influence of customer satisfaction on Grab services in Malaysia. International Journal of Tourism and Hospitality in Asia Pasific (IJTHAP), 3(2), 26-37.

  • Anderson, D. N. (2014). “Not just a taxi”? For-profit ridesharing, driver strategies, and VMT. Transportation, 41(5), 1099-1117.

  • Bohang, F. K. (2017). Berapa jumlah pengguna dan pengemudi Go-Jek? [How many Go-Jek users and drivers?]. Retrieved January 18, 2021, from

  • Caulfield, B. (2009). Estimating the environmental benefits of ride-sharing: A case study of Dublin. Transportation Research Part D: Transportation Environment, 14(7), 527-531.

  • Chan, N., & Shaheen, S. A. (2012). Ridesharing in North America: Past, present, and future. Transportation Reviews, 32(1), 93-112.

  • Cheng, Y. H., & Chen, S. Y. (2015). Perceived accessibility, mobility, and connectivity of public transportation systems. Transportation Research Part A: Policy and Practice, 77, 386-403.

  • Efthymiou, D., Antoniou, C., & Waddell, P. (2013). Factors affecting the adoption of vehicle sharing systems by young drivers. Transport Policy, 29, 64-73.

  • (2019). A complete guide for GoRide’s passenger insurance claim. Retrieved June 04, 2021, from

  • GrabCarMalaysia. (2018). About GrabCar. Retrieved February 06, 2021, from

  • Hall, J. V., & Krueger, A. B. (2016). An analysis of the labor market for Uber’s driver partners in the United States. National Bureau of Economic Research.

  • Henao, A. (2017). Impacts of ridesourcing - Lyft and Uber - On transportation including VMT, mode replacement, parking, and travel behavior. University of Colorado.

  • Hou, J., Zhao, H., Zhao, X., & Zhang, J. (2016). Predicting mobile user’s behaviors and locations using dynamic Bayesian networks. Journal of Management Analytics, 3(3), 191-205.

  • Jaśkiewicz, M., & Besta, T. (2014). Heart and mind in public transport: Analysis of motives, satisfaction and psychological correlates of public transportation usage in the Gdańsk-Sopot-Gdynia Tricity Agglomeration in Poland. Transportation Research Part F: Traffic Psychology and Behaviour, 26, 92-101.

  • Lavieri, P. S., Dias, F. F., Juri, N. R., Kuhr, J., & Bhat, C. R. (2018). A model of ridesourcing demand generation and distribution. Transportation Research Record Journal of the Transportation Research Board, 2672(46), 31-40.

  • Leedy, P. D., & Ormrod, J. E. (2010). Practical research: Planning and design. Pearson Education.

  • Lekshmi, G. R. A., Landge, V. S., & Kumar, V. S. (2016). Activity based travel demand modeling of Thiruvananthapuram urban area. Transportation Research Procedia, 17, 498-505.

  • Morency, C. (2007). The ambivalence of ridesharing. Transportation, 34(2), 239-253.

  • Phun, V. K., Masui, R., & Yai, T. (2018). Operational Characteristics of paratransit services with ride-hailing apps in Asian developing cities: The Phnom Penh case. Journal of Transportation Technologies, 8(04), 291-311.

  • Rayle, L., Shaheen, S., Chan, N., Dai, D., & Cervero, R. (2014). Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco. Transport Policy, 45, 168-178.

  • Regina, R., & Clewlow, G. S. (2018). Disruptive transportation: The adoption, utilization, and impacts of ride-hailing in the United States. Institute of Transportation Studies.

  • Ristantia, N. S., & Hayah, Z. (2018). Smart mobility dalam pengembangan transportasi berbasis aplikasi online di Indonesia [Smart mobility in transportation development based on online application in Indonesia]. Ruang, 4(3), 237-246.

  • Rithoma, A. R., & Rakhmatulloh, A. R. (2013). Kajian rute angkutan umum di Banyumanik Semarang terkait transportasi yang berkelanjutan [A study of public transportation routes in banyumanik semarang regarding sustainable transportation]. Jurnal Pembangunan Wilayah dan Kota, 9(1), 65-73.

  • Sakaran, S. S., Noor, H. M., & Eboy, O. V. (2018). Socioeconomic factors that affect usage of Grabcar services in Kinabalu City, Sabah. Malaysian Journal of Business and Economics, 5(2), 65-77.

  • Shaheen, S., Cohen, A., & Zohdy, I. (2016). Shared mobility: Current practices and guiding principles. (No. FHWA-HOP-16-022). Federal Highway Administration.

  • Šimeček, M. (2019). Discrete choice analysis of travel behaviour. Transactions on Transport Sciences, 10(1), 5-9.

  • Smart, R., Rowe, B., Hawken, A., Kleiman, M., Mladenovic, N., Gehred, P., & Manning, C. (2015). Faster and cheaper: How ride-sourcing fills a gap in low-income Los Angeles neighborhoods faster and cheaper. BOTEC Analysis Corp.

  • Sukma. D. (2016). Data Gfk: 9 dari 10 orang Indonesia internetan lewat smartphone [Gfk data: 9 out of 10 Indonesians surf through smartphones]. Retrieved February 12, 2021, from

  • Zhao, M., Yin, L., An, S., Wang, J., & Feng, D. (2018). Ridesharing problem with flexible pickup and delivery locations for app-based transportation service: Mathematical modeling and decomposition methods. Hindawi Journal of Advanced Transportation, 2018, Article 6430950.

ISSN 0128-7680

e-ISSN 2231-8526

Article ID


Download Full Article PDF

Share this article

Recent Articles